Machine Learning for Auditors

Part I. Trusted Advisors.- 1. Three Lines of Defense.- 2. Common Audit Challenges.- 3. Existing Solutions.- 4. Data Analytics.- 5. Analytics Structure & Environment.- Part II. Understanding Artificial Intelligence.- 6. Introduction to AI, Data Science, and Machine Learning.- 7. Myths and Misconceptions.- 8. Trust, but Verify.- 9. Machine Learning Fundamentals.- 10. Data Lakes.- 11. Leveraging the Cloud.- 12. SCADA and Operational Technology.- Part III. Storytelling.- 13. What is Storytelling?.- 14. Why Storytelling?.- 15. When to Use Storytelling.- 16. Types of Visualizations.- 17. Effective Stories.- 18. Storytelling Tools.- 19. Storytelling in Auditing.- Part IV. Implementation Recipes.- 20. How to Use the Recipes.- 21. Fraud and Anomaly Detection.- 22. Access Management.- 23. Project Management.- 24. Data Exploration.- 25. Vendor Duplicate Payments.- 26. CAATs 2.0.- 27. Log Analysis.- 28. Concluding Remarks.

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• Aprendizagem mecânica
• Algoritmos e estruturas de dados
• Inteligência artificial

Auditng;Storytelling;Trusted Advisors;Predictive Models;Data Analytics;Fraud Detection;Artificial Intelligence (AI);Machine Learning (ML);Data Science;Internal Auditing;Lines of Defense;Anomaly Detection;Access Management